Package: aghermann Version: 1.0.9-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1585 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcairo2 (>= 1.2.4), libconfig++9v5, libfftw3-double3, libgcc1 (>= 1:3.0), libglib2.0-0 (>= 2.31.18), libgomp1 (>= 4.9), libgsl2, libgtk-3-0 (>= 3.3.16), libitpp8v5, liblua5.2-0, libpango-1.0-0 (>= 1.14.0), libsamplerate0 (>= 0.1.7), libstdc++6 (>= 5.2), libunique-3.0-0 (>= 2.90.1), libvte-2.91-0 Suggests: edfbrowser Homepage: http://johnhommer.com/academic/code/aghermann Priority: optional Section: science Filename: pool/main/a/aghermann/aghermann_1.0.9-1~nd16.04+1_amd64.deb Size: 515556 SHA256: be37ff500bc8bd6e095632ffc69c44e8f5cd1ef7ad4f61512e8f2cf5dfd4a031 SHA1: ce1ff44f638fe636a0a59990beef1866de27b1ba MD5sum: a5a8e29e30a090b44ce81bd20709c402 Description: Sleep-research experiment manager Aghermann is a program designed around a common workflow in sleep-research, complete with scoring facility; cairo subpixel drawing on screen or to file; conventional PSD and EEG Micrcontinuity profiles; Independent Component Analysis; artifact detection; and Process S simulation following Achermann et al, 1993. Package: cde Version: 0.1+git9-g551e54d-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1019 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.pgbovine.net/cde.html Priority: optional Section: utils Filename: pool/main/c/cde/cde_0.1+git9-g551e54d-1~nd+1+nd16.04+1_amd64.deb Size: 146038 SHA256: eb56362a6b3ce0989408660070e532c3daf16c3c2b3370fa3f0a72482b65d6ac SHA1: 2f18dadcc4d3237870e8d22c399dc1001e0ac009 MD5sum: 3e45cf198b6c729ae80dd94f03474114 Description: package everything required to execute a Linux command on another computer CDEpack (Code, Data, and Environment packaging) is a tool that automatically packages up everything required to execute a Linux command on another computer without any installation or configuration. A command can range from something as simple as a command-line utility to a sophisticated GUI application with 3D graphics. The only requirement is that the other computer have the same hardware architecture (e.g., x86) and major kernel version (e.g., 2.6.X) as yours. CDEpack allows you to easily run programs without the dependency hell that inevitably occurs when attempting to install software or libraries. . Typical use cases: 1. Quickly share prototype software 2. Try out software in non-native environments 3. Perform reproducible research 4. Instantly deploy applications to cluster or cloud computing 5. Submit executable bug reports 6. Package class programming assignments 7. Easily collaborate on coding projects Package: cnrun-tools Source: cnrun Version: 2.0.3-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 64 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libcnrun2 (>= 2.0.0), libgcc1 (>= 1:3.0), libgsl2, libstdc++6 (>= 5.2) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/cnrun-tools_2.0.3-1~nd+1+nd16.04+1_amd64.deb Size: 17850 SHA256: a917d70432e793890f8ced9f7349d46503736209f286b4b22b78ea54026cb9ab SHA1: 037afa888a1c76cc1dd70ccf2fc57ed54583e441 MD5sum: be7e4c06c618ef3dc1100a6225927632 Description: NeuroML-capable neuronal network simulator (tools) CNrun is a neuronal network simulator implemented as a Lua package. This package contains two standalone tools (hh-latency-estimator and spike2sdf) that may be of interest to CNrun users. . See lua-cnrun description for extended description. Package: dcm2niix Version: 0.20150909.1+git1-g8914c07-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Team Installed-Size: 200 Depends: neurodebian-popularity-contest, libc6 (>= 2.14) Homepage: http://www.mccauslandcenter.sc.edu/CRNL/tools/dcm2niix Priority: optional Section: science Filename: pool/main/d/dcm2niix/dcm2niix_0.20150909.1+git1-g8914c07-1~nd+1+nd16.04+1_amd64.deb Size: 87796 SHA256: 39593c3732a2490dd3ba10b8bb26ebd337ebd16ba7f31db594b897d802b6825e SHA1: 0c3fa9d8b14c7ab214dfdd64c22b1cefbd9e47c2 MD5sum: 77884eaf68485bcae20ae2502cf57f26 Description: converts DICOM and PAR/REC files into the NIfTI format This is the successor of the well-known dcm2nii program. it aims to provide same functionality albeit with much faster operation. This is a new tool that is not yet well tested, and does not handle ancient proprietary formats. Use with care. Package: debruijn Version: 1.6-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 159 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfftw3-double3, libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.cfn.upenn.edu/aguirre/wiki/public:de_bruijn_software Priority: extra Section: science Filename: pool/main/d/debruijn/debruijn_1.6-1~nd+1+nd16.04+1_amd64.deb Size: 38404 SHA256: 4fb44a4b64ebac715085eedc85f4b47ec9b8e642670af3ea6aac74ad3a1b717d SHA1: c80b3c636dcaae3c569696434d7d3e0fddc25544 MD5sum: b591bd9be2b09aef38c2a05fd449a773 Description: De Bruijn cycle generator Stimulus counter-balance is important for many experimental designs. This command-line software creates De Bruijn cycles, which are pseudo-random sequences with arbitrary levels of counterbalance. "Path-guided" de Bruijn cycles may also be created. These sequences encode a hypothesized neural modulation at specified temporal frequencies, and have enhanced detection power for BOLD fMRI experiments. Package: eeglab11-sampledata Source: eeglab11 Version: 11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8117 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/e/eeglab11/eeglab11-sampledata_11.0.0.0~b~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 7059424 SHA256: 3f090fdf3072e4e5b6ac524be1fff62f6d940c0e49f39e0843ba76d43e5b7d2b SHA1: 3f7081f142023ddee661a2980ff92df8a18bf7fe MD5sum: b9da13b2959435f2ec53d8cfda008794 Description: sample EEG data for EEGLAB tutorials EEGLAB is sofwware for processing continuous or event-related EEG or other physiological data. . This package provide some tutorial data files shipped with the EEGLAB distribution. Package: fail2ban Version: 0.9.4-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1199 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), init-system-helpers (>= 1.18~), lsb-base (>= 2.0-7) Recommends: python, iptables, whois, python3-pyinotify, python3-systemd Suggests: mailx, system-log-daemon, monit Homepage: http://www.fail2ban.org Priority: optional Section: net Filename: pool/main/f/fail2ban/fail2ban_0.9.4-1~nd+1+nd16.04+1_all.deb Size: 249598 SHA256: 0a64e615ff52326ea77f03f5fddffb0952cd3ec3937d4092476bc86ab2eba8d4 SHA1: c20a8d4f5c5ac3e99d3ce401380fdcc1af9074ec MD5sum: 3a1f0e5b6e59e048c5e9abde8183f0e8 Description: ban hosts that cause multiple authentication errors Fail2ban monitors log files (e.g. /var/log/auth.log, /var/log/apache/access.log) and temporarily or persistently bans failure-prone addresses by updating existing firewall rules. Fail2ban allows easy specification of different actions to be taken such as to ban an IP using iptables or hostsdeny rules, or simply to send a notification email. . By default, it comes with filter expressions for various services (sshd, apache, qmail, proftpd, sasl etc.) but configuration can be easily extended for monitoring any other text file. All filters and actions are given in the config files, thus fail2ban can be adopted to be used with a variety of files and firewalls. Following recommends are listed: . - iptables -- default installation uses iptables for banning. You most probably need it - whois -- used by a number of *mail-whois* actions to send notification emails with whois information about attacker hosts. Unless you will use those you don't need whois - python3-pyinotify -- unless you monitor services logs via systemd, you need pyinotify for efficient monitoring for log files changes Package: fsl-melview Source: melview Version: 1.0.1+git9-ge661e05~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73 Depends: neurodebian-popularity-contest, python-matplotlib, python-nibabel, python-numpy, python-pkg-resources, python-scipy, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-pyface, python-traits, python-traitsui, python-enthoughtbase Suggests: fsl-core Homepage: http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Melview Priority: optional Section: science Filename: pool/main/m/melview/fsl-melview_1.0.1+git9-ge661e05~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 13946 SHA256: 98fec451744471ae6b47ee84ac52821b45ffd63401f9f29586a9aa6be46a8702 SHA1: 0fb8488befc01e715be4378c0affa5f4d8bce34c MD5sum: 7b7b1bf6546af8b8bcfa435171ebfc89 Description: viewer for the output of FSL's MELODIC This viewer can be used to facilitate manual inspection and classification of ICA components computed by MELODIC. As such, it is suited to generate hand-curated labels for FSL's ICA-based denoising tool FIX. Python-Version: 2.7 Package: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6807 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libgcc1 (>= 1:4.0), libnewmat10ldbl, libnifti2, libqt4-qt3support (>= 4:4.5.3), libqt4-xml (>= 4:4.5.3), libqtcore4 (>= 4:4.7.0~beta1), libqtgui4 (>= 4:4.7.0~beta1), libqwt5-qt4, libstdc++6 (>= 5.2), libvtk5.10, libvtk5.10-qt4 Recommends: fslview-doc, qt-assistant-compat Suggests: fsl-atlases Conflicts: fsl-fslview Replaces: fsl-fslview Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: science Filename: pool/main/f/fslview/fslview_4.0.1-6~nd+1+nd16.04+1_amd64.deb Size: 1344678 SHA256: e63635f648e66f1ed1a8ce622bd7510aa5406dab67da1296ac9bf2ebe683dfc7 SHA1: 1ef5299926d994293e44554757b29d508c88482c MD5sum: 7a00919d11c047c4e4e3fd90add99cc8 Description: viewer for (f)MRI and DTI data This package provides a viewer for 3d and 4d MRI data as well as DTI images. FSLView is able to display ANALYZE and NIFTI files. The viewer supports multiple 2d viewing modes (orthogonal, lightbox or single slices), but also 3d volume rendering. Additionally FSLView is able to visualize timeseries and can overlay metrical and stereotaxic atlas data. . FSLView is part of FSL. Package: fslview-doc Source: fslview Version: 4.0.1-6~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2930 Depends: neurodebian-popularity-contest Homepage: http://www.fmrib.ox.ac.uk/fsl/fslview Priority: optional Section: doc Filename: pool/main/f/fslview/fslview-doc_4.0.1-6~nd+1+nd16.04+1_all.deb Size: 2227648 SHA256: d85f59cee9b040e9680c9817ee0e831d88dca517d2880029a7e9674aead08469 SHA1: 326b580203ce06c723591e460854d73845119293 MD5sum: 9b50fc95856220ca1a5876e4772eff2f Description: Documentation for FSLView This package provides the online documentation for FSLView. . FSLView is part of FSL. Package: git-annex-standalone Source: git-annex Version: 6.20160425+gitgffe2ea2-1~ndall+1 Architecture: amd64 Maintainer: Richard Hartmann Installed-Size: 405869 Depends: git, openssh-client Recommends: lsof, gnupg, bind9-host, quvi, git-remote-gcrypt (>= 0.20130908-6), nocache, aria2 Suggests: graphviz, bup, tahoe-lafs, libnss-mdns Conflicts: git-annex Provides: git-annex Homepage: http://git-annex.branchable.com/ Priority: optional Section: utils Filename: pool/main/g/git-annex/git-annex-standalone_6.20160425+gitgffe2ea2-1~ndall+1_amd64.deb Size: 29197342 SHA256: ce4f5c37a9ce4a166b3f69fc483c21856ef38df74e0ed25947a318e6693c47e1 SHA1: ada490a1106c0e5753d7cc280a26b8cbced95b99 MD5sum: a7e67246bbf11ff715609c6681d1d54e Description: manage files with git, without checking their contents into git -- standalone build git-annex allows managing files with git, without checking the file contents into git. While that may seem paradoxical, it is useful when dealing with files larger than git can currently easily handle, whether due to limitations in memory, time, or disk space. . It can store large files in many places, from local hard drives, to a large number of cloud storage services, including S3, WebDAV, and rsync, with a dozen cloud storage providers usable via plugins. Files can be stored encrypted with gpg, so that the cloud storage provider cannot see your data. git-annex keeps track of where each file is stored, so it knows how many copies are available, and has many facilities to ensure your data is preserved. . git-annex can also be used to keep a folder in sync between computers, noticing when files are changed, and automatically committing them to git and transferring them to other computers. The git-annex webapp makes it easy to set up and use git-annex this way. . This package provides a standalone bundle build of git-annex, which should be installable on any more or less recent Debian or Ubuntu release. Package: heudiconv Version: 0.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 49 Depends: neurodebian-popularity-contest, python, python-dcmstack, python-dicom, python-nibabel, python-numpy, python-nipype Recommends: mricron Homepage: https://github.com/nipy/heudiconv Priority: optional Section: science Filename: pool/main/h/heudiconv/heudiconv_0.1-1~nd+1+nd16.04+1_all.deb Size: 10286 SHA256: b869501f708fea57cfd20fd4325c042865373309c23439a3fc68da089e2821f3 SHA1: 1d3abeac3233e632cf971f22e066c6764272f9a3 MD5sum: 2981f738670efec821e5b4daeb773c86 Description: DICOM converter with support for structure heuristics This is a flexible dicom converter for organizing brain imaging data into structured directory layouts. It allows for flexible directory layouts and naming schemes through customizable heuristics implementations. It only converts the necessary dicoms, not everything in a directory. It tracks the provenance of the conversion from dicom to nifti in w3c prov format. Package: incf-nidash-oneclick-clients Source: incf-nidash-oneclick Version: 2.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 39 Depends: neurodebian-popularity-contest, python (>= 2.5.0), python-dicom, dcmtk, python-httplib2 Homepage: http://xnat.incf.org/ Priority: extra Section: science Filename: pool/main/i/incf-nidash-oneclick/incf-nidash-oneclick-clients_2.0-1~nd+1+nd16.04+1_all.deb Size: 9092 SHA256: 3768f288d0fb7988e227131b3e41a31c00436992b06d2b18e8113e0db08835c0 SHA1: 65c2eeeeb2ec075ec99aecec567a613b9ed2343c MD5sum: 4ff78d0c6fe0960cbf435512258152c0 Description: utility for pushing DICOM data to the INCF datasharing server A command line utility for anonymizing and sending DICOM data to the XNAT image database at the International Neuroinformatics Coordinating Facility (INCF). This tool is maintained by the INCF NeuroImaging DataSharing (NIDASH) task force. Package: ismrmrd-schema Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 25 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-schema_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 5088 SHA256: 5336188e50c28a623d14ce0305ec77a4efef641cdef4c53c5e52157daf080def SHA1: 3ec074921fdde47d6c380e07226bacd940068f41 MD5sum: 349af0ebe53b5ed02810a3874940a35c Description: ISMRM Raw Data format (ISMRMRD) - XML schema The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the XML schema. Package: ismrmrd-tools Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 419 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1), libboost-program-options1.58.0, libc6 (>= 2.14), libfftw3-single3, libgcc1 (>= 1:4.0), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/ismrmrd-tools_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 121502 SHA256: 78302d6acdcf63e8083196cc0edd2f0a98d7204d8f816753b250d027125383a4 SHA1: 8f50df9dca9e2dbf195d8bb277ae7aea5a6131d7 MD5sum: 3f44b7ab42956260ceb8b5c4571295b5 Description: ISMRM Raw Data format (ISMRMRD) - binaries The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the binaries. Package: libcnrun2 Source: cnrun Version: 2.0.3-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 279 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgsl2, libstdc++6 (>= 5.2), libxml2 (>= 2.7.4) Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/libcnrun2_2.0.3-1~nd+1+nd16.04+1_amd64.deb Size: 78018 SHA256: 572dfbdd0f5fb77b0c9b52c5c933ff17f69d5397f4fc27ec8f6e9af2b82ca531 SHA1: 1137741e663655d14fd4ad8f81de44c0082fbc5f MD5sum: cbcef38bd74be2775b7e9d514e07c954 Description: NeuroML-capable neuronal network simulator (shared lib) CNrun is a neuronal network simulator implemented as a Lua package. This package contains shared libraries. . See lua-cnrun description for extended description. Package: libcnrun2-dev Source: cnrun Version: 2.0.3-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 137 Depends: neurodebian-popularity-contest, libcnrun2 (= 2.0.3-1~nd+1+nd16.04+1) Suggests: pkg-config Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: libdevel Filename: pool/main/c/cnrun/libcnrun2-dev_2.0.3-1~nd+1+nd16.04+1_amd64.deb Size: 21292 SHA256: 4d676c52f7d4afeaf4837df5154eb15fd4f59e3ebaa80298a2a18ee46838d553 SHA1: 4e2e1aec3b2336c1467922b5c995c163ed43d806 MD5sum: e586fc5ec9de55061515ba8b55fae3cd Description: NeuroML-capable neuronal network simulator (development files) CNrun is a neuronal network simulator implemented as a Lua package. This package contains development files. . See lua-licnrun description for extended description. Package: libdrawtk-dev Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1+nd16.04+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libdevel Filename: pool/main/d/drawtk/libdrawtk-dev_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 40838 SHA256: f5feeff6952ddeb62dd87daf609d42a85fd1256793c02cff655a28c5c1135527 SHA1: 25c2d35f4e1bcce2638318b5dd68f1779ac56b6c MD5sum: 732f85a397a9c47b3ecf6d33e0237aed Description: Library to simple and efficient 2D drawings (development files) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package contains the files needed to compile and link programs which use drawtk. Package: libdrawtk0 Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 74 Depends: neurodebian-popularity-contest, libc6 (>= 2.17), libfontconfig1 (>= 2.11.94), libfreeimage3, libfreetype6 (>= 2.2.1), libgl1-mesa-glx | libgl1, libglib2.0-0 (>= 2.12.0), libgstreamer-plugins-base0.10-0 (>= 0.10.23), libgstreamer0.10-0 (>= 0.10.25), libsdl1.2debian (>= 1.2.11) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: libs Filename: pool/main/d/drawtk/libdrawtk0_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 22950 SHA256: a4ec511db2ae929dca64942b19dde14e37cc930fbba040f3540fc05c2350fb89 SHA1: ef54e9475cb903a84c59f9205712fe358ad3dbbb MD5sum: a9c93cacded8f138c4be6762e3626d06 Description: Library to simple and efficient 2D drawings This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. Package: libdrawtk0-dbg Source: drawtk Version: 2.0-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 97 Depends: neurodebian-popularity-contest, libdrawtk0 (= 2.0-2~nd+1+nd16.04+1) Multi-Arch: same Homepage: http://cnbi.epfl.ch/software/drawtk.html Priority: extra Section: debug Filename: pool/main/d/drawtk/libdrawtk0-dbg_2.0-2~nd+1+nd16.04+1_amd64.deb Size: 78044 SHA256: 2c4fb8f4d282ef67ab0f9a567faa2500c17c5c84abfc554680619e038658e98a SHA1: 6fc79165c562d2cabf4a83e7d168a9f8e50d2813 MD5sum: 35283c42813f7ba96f1f23cd7f1b2276 Description: Library to simple and efficient 2D drawings (debugging symbols) This package provides an C library to perform efficient 2D drawings. The drawing is done by OpenGL allowing fast and nice rendering of basic shapes, text, images and videos. It has been implemented as a thin layer that hides the complexity of the OpenGL library. . This package provides the debugging symbols for the library. Build-Ids: c41828d10c9804b856f1c119e946fc5911d6ba88 Package: libismrmrd-dev Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, ismrmrd-schema, libismrmrd1.3 (= 1.3.2-1~nd+1+nd16.04+1) Suggests: libismrmrd-doc Homepage: http://ismrmrd.github.io/ Priority: optional Section: libdevel Filename: pool/main/i/ismrmrd/libismrmrd-dev_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 13854 SHA256: fce1dcfd5beb5df399ccfb6498202a50a40e0064d01475991f1704a427d2170a SHA1: 02fdb706e684aa870a2a9e72a4c977d1446e85c9 MD5sum: 4381a6b43e5c57caa311110668c0ce39 Description: ISMRM Raw Data format (ISMRMRD) - development files The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the development files. Package: libismrmrd-doc Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1961 Depends: neurodebian-popularity-contest Homepage: http://ismrmrd.github.io/ Priority: optional Section: doc Filename: pool/main/i/ismrmrd/libismrmrd-doc_1.3.2-1~nd+1+nd16.04+1_all.deb Size: 157932 SHA256: 2f24afbb9b3936557b75c9f69827bad728cd057e3a34aac31466f47d948cb216 SHA1: accfe2ca334b0b97c931424db47de6e435fae5f7 MD5sum: f81b7692ba25e05413fe88a248cc60a4 Description: ISMRM Raw Data format (ISMRMRD) - documentation The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the documentation. Package: libismrmrd1.3 Source: ismrmrd Version: 1.3.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 340 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libhdf5-10, libpugixml1v5 (>= 1.4), libstdc++6 (>= 5.2) Homepage: http://ismrmrd.github.io/ Priority: optional Section: science Filename: pool/main/i/ismrmrd/libismrmrd1.3_1.3.2-1~nd+1+nd16.04+1_amd64.deb Size: 77426 SHA256: 4f6d5e547780343ed4e69c90cc6758d33dd63726c043cfb2f9aedb8e4fac976c SHA1: 534f1d6d4992eadf722ca065ddc80d68a863133e MD5sum: b833217e3b785a0eec90d15a348a51f0 Description: ISMRM Raw Data format (ISMRMRD) - shared library The ISMRMRD format combines a mix of flexible data structures (XML header) and fixed structures (equivalent to C-structs) to represent MRI data. . In addition, the ISMRMRD format also specifies an image header for storing reconstructed images and the accompanying C++ library provides a convenient way of writing such images into HDF5 files along with generic arrays for storing less well defined data structures, e.g. coil sensitivity maps or other calibration data. . This package provides the shared library. Package: libvrpn-dev Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 719 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libdevel Filename: pool/main/v/vrpn/libvrpn-dev_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 141804 SHA256: 94288ad8b34fc9e5153c428b991bb393ceb4639f25155e419474d6e7dc5d73ab SHA1: 3ea2e3e1d120cfe2ced2b587f4b52e9a3f6778cf MD5sum: 5f1fe237ba0bfa83ebbf919e677b3488 Description: Virtual Reality Peripheral Network (development files) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the development files Package: libvrpn0 Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 517 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpn0_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 140886 SHA256: 609bc6cbce66ff9dfb18a6bf219eb48b0843e6668cb05464b95c4a0dec57a9a9 SHA1: b8866c2e347c0a7732ac1aa24453fdb4db5510b5 MD5sum: 75fdd8f2faf079608577afd2e9315aa4 Description: Virtual Reality Peripheral Network (client library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the client shared library Package: libvrpnserver0 Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1274 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: libs Filename: pool/main/v/vrpn/libvrpnserver0_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 328612 SHA256: c8f1275c4aacd25a2468ce435b019ffd5061444d29abb8288a60ff869e9bc12b SHA1: 8798dafcffac3fd5625874b3109acdcfa435e74d MD5sum: fc61b3041dbf76ab8dc9baff10c7c159 Description: Virtual Reality Peripheral Network (server library) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the shared library use in the VRPN server Package: libvtk-dicom-java Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 277 Depends: neurodebian-popularity-contest, libvtk-java, libc6 (>= 2.4), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10 Suggests: java-virtual-machine Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: java Filename: pool/main/v/vtk-dicom/libvtk-dicom-java_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 74226 SHA256: 23c4508e06435a593df82eb7ce2ed01fb266f8a181cda9ceae84b95f61f82190 SHA1: 38662d93b0426d0f1fcb71df41cd78d4bd59ed8f MD5sum: 3984760e7a13df1cd289e15835d484ab Description: DICOM for VTK - java This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Java 1.5 bindings Package: libvtk-dicom0.5 Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1786 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgdcm2.6, libstdc++6 (>= 5.2), libvtk5.10, zlib1g (>= 1:1.2.3.4) Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libs Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 445290 SHA256: a6f8e6f152d55de7e111d1725d33fc240ed5d63e543288fc46f23c57114c7dd4 SHA1: 489f5ae091cc6574ac92c344cad671eea9a48741 MD5sum: 2316cc705030caf3896c8e1dd4be9d2c Description: DICOM for VTK - lib This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Libraries for runtime applications Package: libvtk-dicom0.5-dev Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 565 Depends: neurodebian-popularity-contest, libvtk-dicom0.5 (= 0.5.5-2~nd+1+nd16.04+1) Conflicts: libvtk-dicom0.4-dev Replaces: libvtk-dicom0.4-dev Provides: libvtk-dicom-dev Multi-Arch: same Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: libdevel Filename: pool/main/v/vtk-dicom/libvtk-dicom0.5-dev_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 81110 SHA256: 4834857f522b21905239609c60952b1baf8cd1032446672eca6954a03b6776cb SHA1: 4c3664ff72f9f8264fc222c34bc8ec8d8dc2cdb1 MD5sum: 329447cfc41445c3f1f55dc28448c1e5 Description: DICOM for VTK - dev This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Development headers Package: lua-cnrun Source: cnrun Version: 2.0.3-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 120 Depends: neurodebian-popularity-contest, libcnrun2, lua5.1 | lua5.2 Suggests: gnuplot Homepage: http://johnhommer.com/academic/code/cnrun Priority: optional Section: science Filename: pool/main/c/cnrun/lua-cnrun_2.0.3-1~nd+1+nd16.04+1_amd64.deb Size: 37888 SHA256: 3e7a9a9b28df13691e29bdf5fad2b411a7fb105cc30cb4330020798ae6aecd55 SHA1: 66498589689e98ae5cefd879017e1b7033fe1ac9 MD5sum: c213fe02b84315f055b6d4c39108b09a Description: NeuroML-capable neuronal network simulator (Lua package) CNrun is a neuronal network simulator, with these features: * a conductance- and rate-based Hodgkin-Huxley neurons, a Rall and Alpha-Beta synapses; * a 6-5 Runge-Kutta integration method: slow but precise, adjustable; * Poisson, Van der Pol, Colpitts oscillators and interface for external stimulation sources; * NeuroML network topology import/export; * logging state variables, spikes; * implemented as a Lua module, for scripting model behaviour (e.g., to enable plastic processes regulated by model state); * interaction (topology push/pull, async connections) with other cnrun models running elsewhere on a network, with interactions (planned). . Note that there is no `cnrun' executable, which existed in cnrun-1.*. Instead, you write a script for your simulation in Lua, and execute it as detailed in /usr/share/lua-cnrun/examples/example1.lua. Package: mialmpick Version: 0.2.10-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgdk-pixbuf2.0-0 (>= 2.22.0), libgl1-mesa-glx | libgl1, libglade2-0 (>= 1:2.6.4-2~), libglib2.0-0 (>= 2.41.1), libglu1-mesa | libglu1, libgnomeui-0 (>= 2.22.0), libgtk2.0-0 (>= 2.20.0), libgtkglext1, libmialm3 (>= 1.0.7), libpng12-0 (>= 1.2.13-4), libpopt0 (>= 1.14), libvistaio14 (>= 1.2.14), libx11-6 Homepage: http://mia.sourceforge.net Priority: optional Section: science Filename: pool/main/m/mialmpick/mialmpick_0.2.10-1~nd+1+nd16.04+1_amd64.deb Size: 68744 SHA256: e6edea5d6279b95758d3d8fcef82495d58ba2d0f79cdb52b50efcfd096a8dc36 SHA1: 37aa16f4e74dbbf39a3591d3d351dc18cf070c7c MD5sum: d8cfe7b9bc985019b8a2a6c250623148 Description: Tools for landmark picking in 3D volume data sets This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. Package: mialmpick-dbg Source: mialmpick Version: 0.2.10-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 198 Depends: neurodebian-popularity-contest, mialmpick (= 0.2.10-1~nd+1+nd16.04+1) Homepage: http://mia.sourceforge.net Priority: extra Section: debug Filename: pool/main/m/mialmpick/mialmpick-dbg_0.2.10-1~nd+1+nd16.04+1_amd64.deb Size: 160232 SHA256: f8215de9087fcd45d680f4c99bdbb04b68e9f52eb5bb7a08ecc352e41708753f SHA1: 2923ca8c1a2f24708c36bc3dcd0fab49f8bf8eef MD5sum: fe81542df04c8f3de1ac5730f5b41b56 Description: Debug information landmark picking tool mialmpick This tool provides a simple 3D renderer that can visualize surfaces directly from 3D volumes and can be used to set 3D landmarks. It is best suited for CT data sets. This package provides the debug information. Build-Ids: 70b701f30b49c51e532be8647e4165bee8a3bae2 Package: mridefacer Version: 0.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 647 Depends: fsl-5.0-core | fsl-core Homepage: https://github.com/hanke/mridefacer Priority: optional Section: science Filename: pool/main/m/mridefacer/mridefacer_0.1-1~nd+1+nd16.04+1_all.deb Size: 637084 SHA256: 61171ad1d66be396e47ff2b9fd15f81f89f9e98a86ac5a13348dccf50c4e9ef7 SHA1: 7a0a9de78fd5f5b729443093360f9499e1f8ec92 MD5sum: 7092b1a40c46bc624b17e265611cfefc Description: de-identification of MRI data This tool creates a de-face mask for volumetric images by aligning a template mask to the input. Such a mask can be used to remove image data from the vicinity of the facial surface, the auricles, and teeth in order to prevent a possible identification of a person based on these features. mrideface can process individual or series of images. In the latter case, the computed transformation between template image and input image will be updated incrementally for the next image in the series. This feature is most suitable for processing images that have been recorded in temporal succession. Package: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 67 Depends: neurodebian-popularity-contest, libc6 (>= 2.15), debconf (>= 0.5) | debconf-2.0 Suggests: netselect-apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect_0.3.ds1-25~nd+1+nd16.04+1_amd64.deb Size: 31150 SHA256: 044e5be3e9c3d37d3d9b6d7277091323144dbcaf24a6fa473d2280d9649bf38e SHA1: 9a9e2c6319c86b91d886207a1dfb6609b10dc572 MD5sum: 5fe7ee1c9d627c00f7606510809930cf Description: speed tester for choosing a fast network server This package provides a utility that can perform parallelized tests on distant servers using either UDP traceroutes or ICMP queries. . It can process a (possibly very long) list of servers, and choose the fastest/closest one automatically. Package: netselect-apt Source: netselect Version: 0.3.ds1-25~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 38 Depends: neurodebian-popularity-contest, wget, netselect (>= 0.3.ds1-17) Recommends: curl Suggests: dpkg-dev Enhances: apt Homepage: http://github.com/apenwarr/netselect Priority: optional Section: net Filename: pool/main/n/netselect/netselect-apt_0.3.ds1-25~nd+1+nd16.04+1_all.deb Size: 16814 SHA256: 22e5cc29f87c08ceb667084f2af3810aaefd1b5fc0828b2f0b0e29cb2a4dc46e SHA1: 90467c75aaba4e464a72ac39884410acc60cfc49 MD5sum: 60f499833563a70a8dc586c029092380 Description: speed tester for choosing a fast Debian mirror This package provides a utility that can choose the best Debian mirror by downloading the full mirror list and using netselect to find the fastest/closest one. . It can output a sources.list(5) file that can be used with package management tools such as apt or aptitude. Package: neurodebian Version: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 88 Depends: python, wget, neurodebian-archive-keyring, debconf (>= 0.5) | debconf-2.0 Recommends: netselect Suggests: neurodebian-desktop, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian_0.37.4~nd+1+nd16.04+1_all.deb Size: 33220 SHA256: 7a291254cef69447223cf23e174be2bb9dde5641d732066e8133103ed477837d SHA1: 026e23734c048805c40e42dd3152d1c5374a05ba MD5sum: 305c5e15259de877b868dd87d20ec7f9 Description: neuroscience-oriented distribution - repository configuration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package enables the NeuroDebian repository on top of a standard Debian or Ubuntu system. Package: neurodebian-archive-keyring Source: neurodebian Version: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 23 Breaks: neurodebian-keyring (<< 0.34~) Replaces: neurodebian-keyring (<< 0.34~) Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-archive-keyring_0.37.4~nd+1+nd16.04+1_all.deb Size: 10212 SHA256: 54f93bb27b10a63d53d5cc56bb5e5bc76e5eda79149dff996860017853bb861e SHA1: aff10204df3e0a20b90cb4ddd78a4132befd1ec8 MD5sum: d3a3a7235f2eb3aa7b806b29d07b8f97 Description: neuroscience-oriented distribution - GnuPG archive keys The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . The NeuroDebian project digitally signs its Release files. This package contains the archive keys used for that. Package: neurodebian-desktop Source: neurodebian Version: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 189 Depends: ssh-askpass-gnome | ssh-askpass, desktop-base, adwaita-icon-theme | gnome-icon-theme, neurodebian-popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-desktop_0.37.4~nd+1+nd16.04+1_all.deb Size: 116286 SHA256: f81556e3bf5b4e5b98aa4ce962bdd588f78bfa30d6f3d02458d0ff2a805d1941 SHA1: deaf7c94a9666e5339092bc603664de59f26d677 MD5sum: 003085b0b9131edee9aa909f5cb8c6d1 Description: neuroscience-oriented distribution - desktop integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides NeuroDebian artwork (icons, background image) and a NeuroDebian menu featuring the most popular neuroscience tools, which will be automatically installed upon initial invocation. Package: neurodebian-dev Source: neurodebian Version: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 109 Depends: devscripts, neurodebian-archive-keyring Recommends: python, zerofree, moreutils, time, ubuntu-keyring, debian-archive-keyring, apt-utils, cowbuilder Suggests: virtualbox-ose, virtualbox-ose-fuse Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-dev_0.37.4~nd+1+nd16.04+1_all.deb Size: 32578 SHA256: 3b86dc568ea07bbcc38a60c30adc9f9e5fb53648f215a33531dc86932d963b49 SHA1: ae3c1ae4a137e5fe852bb475196eaa78fd80f63a MD5sum: bde159eaa3f00b17f487946335abca22 Description: neuroscience-oriented distribution - development tools The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package provides sources and development tools used by NeuroDebian to provide backports for a range of Debian/Ubuntu releases. Package: neurodebian-popularity-contest Source: neurodebian Version: 0.37.4~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 27 Depends: popularity-contest Homepage: http://neuro.debian.net Priority: optional Section: science Filename: pool/main/n/neurodebian/neurodebian-popularity-contest_0.37.4~nd+1+nd16.04+1_all.deb Size: 12254 SHA256: 51221ecc02fffe5cdb87ead95e1d8b2171c95a49640ba0664e81ed7cc5bb62b2 SHA1: df497665fca4e0962d393ea3793ab56efc04a170 MD5sum: ce5743cbdf8ce13b610c6f09a3f5a069 Description: neuroscience-oriented distribution - popcon integration The NeuroDebian project integrates and maintains a variety of software projects within Debian that are useful for neuroscience (such as AFNI, FSL, PsychoPy, etc.) or generic computation (such as HTCondor, pandas, etc.). . This package is a complement to the generic popularity-contest package to enable anonymous submission of usage statistics to NeuroDebian in addition to the popcon submissions to the underlying distribution (either Debian or Ubuntu) popcon server. . Participating in popcon is important for the following reasons: * Popular packages receive more attention from developers; bugs are fixed faster and updates are provided quicker. * It ensures that support is not dropped for a previous release of Debian or Ubuntu while there are active users. * User statistics may be useful for upstream research software developers seeking funding for continued development. . This requires that popcon is activated for the underlying distribution (Debian or Ubuntu), which can be achieved by running "dpkg-reconfigure popularity-contest" as root. Package: nuitka Version: 0.5.21+ds-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 2918 Depends: neurodebian-popularity-contest, g++-4.9 | g++-4.8 | g++-4.7 | g++-4.6 (>= 4.6.1) | g++-4.5 | g++-4.4 | clang (>= 3.0), scons (>= 2.0.0), python-dev (>= 2.6.6-2), python:any (>= 2.7.5-5~) Recommends: python-lxml (>= 2.3), python-qt4 (>= 4.8.6), strace Suggests: ccache Homepage: http://nuitka.net Priority: optional Section: python Filename: pool/main/n/nuitka/nuitka_0.5.21+ds-1~nd16.04+1_all.deb Size: 612002 SHA256: d87d845e3857245e5a579818025556ee256c7daa82da0a34546dc16046af0ff3 SHA1: df6e12ef7b6b901cd6854abdd9b237dadd73c893 MD5sum: 0bbf26aa3309db29a978c21579942572 Description: Python compiler with full language support and CPython compatibility This Python compiler achieves full language compatibility and compiles Python code into compiled objects that are not second class at all. Instead they can be used in the same way as pure Python objects. Package: octave-psychtoolbox-3 Source: psychtoolbox-3 Version: 3.0.12.20160414.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3610 Depends: neurodebian-popularity-contest, octave (>= 3.4.3-1~), freeglut3, libasound2 (>= 1.0.16), libc6 (>= 2.14), libdc1394-22, libfreenect0.5 (>= 1:0.1.1), libgl1-mesa-glx | libgl1, libglew1.13 (>= 1.12.0), libglib2.0-0 (>= 2.12.0), libglu1-mesa | libglu1, libgstreamer-plugins-base1.0-0 (>= 1.0.0), libgstreamer1.0-0 (>= 1.4.0), liboctave3, libopenal1 (>= 1.14), libpciaccess0 (>= 0.8.0+git20071002), libusb-1.0-0 (>= 2:1.0.9), libx11-6 (>= 2:1.2.99.901), libx11-xcb1, libxcb-dri3-0, libxcb1, libxext6, libxfixes3, libxi6 (>= 2:1.2.99.4), libxrandr2 (>= 2:1.2.99.3), libxxf86vm1, psychtoolbox-3-common (= 3.0.12.20160414.dfsg1-1~nd16.04+1), psychtoolbox-3-lib (= 3.0.12.20160414.dfsg1-1~nd16.04+1) Recommends: octave-audio, octave-image, octave-optim, octave-signal, octave-statistics Provides: psychtoolbox, psychtoolbox-3 Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/octave-psychtoolbox-3_3.0.12.20160414.dfsg1-1~nd16.04+1_amd64.deb Size: 747960 SHA256: 8741ec5920e6015c1638e7870922b4929d4faa5fd786889039d1e6fb52999454 SHA1: be3fe860e31503968ff3192c5930e6fb4ffc07ea MD5sum: 1969e63223b4f50d8c8fe1cefb51a1a3 Description: toolbox for vision research -- Octave bindings Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . See also http://www.psychtoolbox.org/UsingPsychtoolboxOnUbuntu for additional information about systems tune-up and initial configuration. . This package contains bindings for Octave. Package: psychopy Version: 1.83.04.dfsg-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 15088 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyglet | python-pygame, python-opengl, python-numpy, python-scipy, python-matplotlib, python-lxml, python-configobj Recommends: python-wxgtk3.0, python-wxgtk2.8, python-pyglet, python-pygame, python-openpyxl, python-opencv, python-imaging, python-serial, python-pyo, python-psutil, python-gevent, python-msgpack, python-yaml, python-xlib, python-pandas, libxxf86vm1, ipython Suggests: python-iolabs, python-pyxid, libavbin0 Conflicts: libavbin0 (= 7-4+b1) Homepage: http://www.psychopy.org Priority: optional Section: science Filename: pool/main/p/psychopy/psychopy_1.83.04.dfsg-2~nd+1+nd16.04+1_all.deb Size: 6133828 SHA256: 7bc5b24a1849eaf939d573157788037c0f1f6a6a54bc84c45b025780d09b207f SHA1: 60bb27e236f204f1f43c10b98e20170e50ac4f60 MD5sum: 269a0abc067dfa3a1d79234abf54295b Description: environment for creating psychology stimuli in Python PsychoPy provides an environment for creating psychology stimuli using Python scripting language. It combines the graphical strengths of OpenGL with easy Python syntax to give psychophysics a free and simple stimulus presentation and control package. . The goal is to provide, for the busy scientist, tools to control timing and windowing and a simple set of pre-packaged stimuli and methods. PsychoPy features . - IDE GUI for coding in a powerful scripting language (Python) - Builder GUI for rapid development of stimulation sequences - Use of hardware-accelerated graphics (OpenGL) - Integration with Spectrascan PR650 for easy monitor calibration - Simple routines for staircase and constant stimuli experimental methods as well as curve-fitting and bootstrapping - Simple (or complex) GUIs via wxPython - Easy interfaces to joysticks, mice, sound cards etc. via PyGame - Video playback (MPG, DivX, AVI, QuickTime, etc.) as stimuli Python-Version: 2.7 Package: psychtoolbox-3-common Source: psychtoolbox-3 Version: 3.0.12.20160414.dfsg1-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 253473 Depends: neurodebian-popularity-contest Recommends: alsa-utils Suggests: gnuplot Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-common_3.0.12.20160414.dfsg1-1~nd16.04+1_all.deb Size: 24209296 SHA256: e8fe891363adc2f05bd8cc6e6dfc6ef56a522b9a78c537d56abe039b6187417a SHA1: 867ffc1ce27b4f7c99987831cd19928515e961cc MD5sum: 6fe139788d0396960445a2690dec5348 Description: toolbox for vision research -- arch/interpreter independent part Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains architecture independent files (such as .m scripts) Package: psychtoolbox-3-dbg Source: psychtoolbox-3 Version: 3.0.12.20160414.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 2939 Depends: neurodebian-popularity-contest, octave-psychtoolbox-3 (= 3.0.12.20160414.dfsg1-1~nd16.04+1) Homepage: http://psychtoolbox.org Priority: extra Section: debug Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-dbg_3.0.12.20160414.dfsg1-1~nd16.04+1_amd64.deb Size: 603186 SHA256: 360a06da6f10597041a6ac9ad45254b1fb26a57065ddefe00ae822cb42499c92 SHA1: 5e4cd6ca91ac6c9bf0b4f7a24eb2fd84d90ec1c7 MD5sum: d58211211bb8f5eebe40032ee196de0c Description: toolbox for vision research -- debug symbols for binaries Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . To ease debugging and troubleshooting this package contains debug symbols for Octave bindings and other binaries. Package: psychtoolbox-3-lib Source: psychtoolbox-3 Version: 3.0.12.20160414.dfsg1-1~nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 190 Depends: neurodebian-popularity-contest, libc6 (>= 2.4), libfontconfig1 (>= 2.11.94), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libglu1-mesa | libglu1, libstdc++6 (>= 4.6) Recommends: gstreamer1.0-plugins-base, gstreamer1.0-plugins-good, gstreamer1.0-plugins-bad, gstreamer1.0-plugins-ugly, gstreamer1.0-libav Homepage: http://psychtoolbox.org Priority: extra Section: science Filename: pool/main/p/psychtoolbox-3/psychtoolbox-3-lib_3.0.12.20160414.dfsg1-1~nd16.04+1_amd64.deb Size: 73044 SHA256: 4d2e8a6926944fc446da1e10c5b931a3d460ee289421a336a52eba256d23ec81 SHA1: df227e033f64f778bc59125691890c7448a11ec2 MD5sum: fd4927737c0fadc3690083d335b8f8cf Description: toolbox for vision research -- arch-specific parts Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU/Octave functions for vision research. It makes it easy to synthesize and show accurately controlled visual and auditory stimuli and interact with the observer. . The Psychophysics Toolbox interfaces between Matlab or Octave and the computer hardware. The Psychtoolbox's core routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical retrace, support millisecond timing, allow access to OpenGL commands, and facilitate the collection of observer responses. Ancillary routines support common needs like color space transformations and the QUEST threshold seeking algorithm. . This package contains additional binaries (tools/dynamic libraries) used by both Octave and Matlab frontends. Package: python-argcomplete Version: 1.0.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 111 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python-argcomplete_1.0.0-1~nd+1+nd16.04+1_all.deb Size: 24608 SHA256: 156b7dbfd8a99d398fe740c822ba51762781af630c9ce000cdebb5622fe4cd2a SHA1: 937a26dd82a75e4b14bb613ae8f6dd187ee9e10b MD5sum: 3f721e38ee6f5930587547ae87875163 Description: bash tab completion for argparse Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 2.x. Package: python-dcmstack Source: dcmstack Version: 0.6.2+git33-gb43919a.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 505 Depends: neurodebian-popularity-contest, python-dicom (>= 0.9.7~), python-nibabel (>= 2.0~), python-numpy, python:any (<< 2.8), python:any (>= 2.7.5-5~), libjs-sphinxdoc (>= 1.0) Provides: python2.7-dcmstack Homepage: https://github.com/moloney/dcmstack Priority: optional Section: python Filename: pool/main/d/dcmstack/python-dcmstack_0.6.2+git33-gb43919a.1-1~nd+1+nd16.04+1_all.deb Size: 77560 SHA256: fb442364f1761b5203c259ef22654f0f4bb883a8eac5dba645ca88b0ec327125 SHA1: 809e0e779921d515682e8f3b543df9321b89650c MD5sum: 307b067807c7a48930ebcc46f0121e7a Description: DICOM to Nifti conversion DICOM to Nifti conversion with the added ability to extract and summarize meta data from the source DICOMs. The meta data can be injected into a Nifti header extension or written out as a JSON formatted text file. . This package provides the Python package, command line tools (dcmstack, and nitool), as well as the documentation in HTML format. Package: python-git Version: 2.0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1570 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python-gitdb (>= 0.6.4), python:any (<< 2.8), python:any (>= 2.7.5-5~) Suggests: python-smmap, python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python-git_2.0.2-1~nd16.04+1_all.deb Size: 288848 SHA256: 5874b2bf64b59c1ffaedeb3496f1ed8144e045e5d28baa5fe0014e0351c014c9 SHA1: 2325b61151d56301934cbd8660339e17b2356072 MD5sum: 20c6d081d52b6c87d60fa85d860e7296 Description: Python library to interact with Git repositories - Python 2.7 python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 2.7 module. Python-Version: 2.7 Package: python-git-doc Source: python-git Version: 2.0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 929 Depends: neurodebian-popularity-contest, libjs-sphinxdoc (>= 1.0) Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: doc Filename: pool/main/p/python-git/python-git-doc_2.0.2-1~nd16.04+1_all.deb Size: 118534 SHA256: aba29ca03a7bdd4569919ef729c6e4e2461d538da47902e23b0cdc68371dfae1 SHA1: d8a126e4a7c70835c41ff384da3dd4ad7a00fbdf MD5sum: 73bc8c1c52a05d0def3f16b27be8dcb0 Description: Python library to interact with Git repositories - docs python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the documentation. Package: python-lda Source: lda Version: 1.0.2-9~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python-lda_1.0.2-9~nd+1+nd16.04+1_amd64.deb Size: 237662 SHA256: f27225dae5ede49f6db3b33d738901167019d32da2e264225201a799191992be SHA1: a0e2612212fc60fe89fa6e89a18324cf58c5b322 MD5sum: 859d71b6198aaf4f79eb8efd737d75bf Description: Topic modeling with latent Dirichlet allocation for Python 3 lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 2.7 module. Package: python-mvpa2 Source: pymvpa2 Version: 2.4.3-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 8373 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy, python-mvpa2-lib (>= 2.4.3-1~nd+1+nd16.04+1) Recommends: python-h5py, python-lxml, python-matplotlib, python-mdp, python-nibabel, python-nipy, python-psutil, python-psyco, python-pywt, python-reportlab, python-scipy, python-sklearn, python-shogun, liblapack-dev, python-pprocess, python-statsmodels, python-joblib, python-duecredit Suggests: fslview, fsl, python-mvpa2-doc, python-nose, python-openopt, python-rpy2 Provides: python2.7-mvpa2 Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2_2.4.3-1~nd+1+nd16.04+1_all.deb Size: 5064896 SHA256: 19a51fb3e9a0a51d90fb6fcd419f1c1fe7a8f041006e7784c4ffd64c08e80433 SHA1: 10b1cdddfa009638156031d5284fe2941f4bf133 MD5sum: 3e3d067511035e1b61f1a278a50fb8ec Description: multivariate pattern analysis with Python v. 2 PyMVPA eases pattern classification analyses of large datasets, with an accent on neuroimaging. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun). . While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets. . This is a package of PyMVPA v.2. Previously released stable version is provided by the python-mvpa package. Python-Version: 2.7 Package: python-mvpa2-doc Source: pymvpa2 Version: 2.4.3-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 34356 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-mvpa2, python-mvpa2-tutorialdata, ipython-notebook Homepage: http://www.pymvpa.org Priority: optional Section: doc Filename: pool/main/p/pymvpa2/python-mvpa2-doc_2.4.3-1~nd+1+nd16.04+1_all.deb Size: 4535668 SHA256: 4da555c9f731067949ab9f2c5b3c618a29369c6c3f022b94ca146ecae200c434 SHA1: 5495291d363831f214fa1cdf6674bcfcf8f72140 MD5sum: 89ec4ac7d7a4521aee3aa66afc42cca7 Description: documentation and examples for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a HTML documentation (tutorial, FAQ etc.), and example scripts. In addition the PyMVPA tutorial is also provided as IPython notebooks. Package: python-mvpa2-lib Source: pymvpa2 Version: 2.4.3-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 136 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.1.1), libsvm3, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9 Provides: python2.7-mvpa2-lib Homepage: http://www.pymvpa.org Priority: optional Section: python Filename: pool/main/p/pymvpa2/python-mvpa2-lib_2.4.3-1~nd+1+nd16.04+1_amd64.deb Size: 48764 SHA256: 366e110aee44bf163db8fe47e9a7800fb7a6d56983857ae80375235a14e3d4e1 SHA1: c3f3b3c191d1c5ddf1e5f09561f3aa79e55d0f1a MD5sum: f63052f37f2b4d261eb54d236be1f5ec Description: low-level implementations and bindings for PyMVPA v. 2 This is an add-on package for the PyMVPA framework. It provides a low-level implementation of an SMLR classifier and custom Python bindings for the LIBSVM library. . This is a package of a development snapshot. The latest released version is provided by the python-mvpa-lib package. Python-Version: 2.7 Package: python-neurosynth Source: neurosynth Version: 0.3-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 115 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-numpy, python-scipy, python-nibabel, python-ply Recommends: python-nose, fsl-mni152-templates Suggests: python-testkraut Homepage: http://neurosynth.org Priority: extra Section: python Filename: pool/main/n/neurosynth/python-neurosynth_0.3-1~nd+1+nd16.04+1_all.deb Size: 28850 SHA256: 35e58bca96796988f7c3097c71ba0e078b6063215ce782dfb2461f30da939f7a SHA1: 37df2d9b9330ef7948d4bb86173b30a9eccaa0ca MD5sum: 6fbc209e0a5e48cd60f07cdbfc7aba56 Description: large-scale synthesis of functional neuroimaging data NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. This Python module at the moment provides functionality for processing the database of collected terms and spatial coordinates to generate associated spatial statistical maps. Package: python-openpyxl Source: openpyxl Version: 2.3.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1323 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-jdcal, python-lxml (>= 3.3.4) | python-et-xmlfile Recommends: python-pytest, python-pil, python-imaging Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python-openpyxl_2.3.0-2~nd16.04+1_all.deb Size: 199220 SHA256: b70affd1599e94a0a0930fb4497a75e7466ed0e7b4f1e4ad1be006c6327e75b2 SHA1: bc62307b04fb297c5e98a1e2a55ff2339524aae8 MD5sum: 90c38c6c2346aab02e8a77c47243a274 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python-pandas Source: pandas Version: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13062 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-dateutil, python-tz, python-numpy (>= 1:1.7~), python-pandas-lib (>= 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1), python-pkg-resources, python-six Recommends: python-scipy, python-matplotlib, python-tables, python-numexpr, python-xlrd, python-statsmodels, python-openpyxl, python-xlwt, python-bs4, python-html5lib, python-lxml Suggests: python-pandas-doc Provides: python2.7-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_all.deb Size: 1761628 SHA256: bdf8a873b0689f85de49043080a66b3db748d23ee249ade8fd1846fdd39dd6c3 SHA1: 51dc91d23ed7d77e7226a51725870de453b229f2 MD5sum: e3af81eb6c0a538bab0f91fdaff1fa44 Description: data structures for "relational" or "labeled" data pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 2 version. Package: python-pandas-doc Source: pandas Version: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 56947 Depends: neurodebian-popularity-contest, libjs-jquery Suggests: python-pandas Homepage: http://pandas.sourceforge.net Priority: optional Section: doc Filename: pool/main/p/pandas/python-pandas-doc_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_all.deb Size: 10937012 SHA256: 5f86809d0b83c1d5fe64fb18b865d454ed30b5e53ab92109238d8abf924035f3 SHA1: aa85840797bfe5ed8d61ffcccf0a8e39fa259d12 MD5sum: 0301c163fcca6afe21e7d31ded207b96 Description: documentation and examples for pandas This package contains documentation and example scripts for python-pandas. Package: python-pandas-lib Source: pandas Version: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6205 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (>= 2.7), python (<< 2.8) Provides: python2.7-pandas-lib Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python-pandas-lib_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_amd64.deb Size: 1566524 SHA256: 5f81173cbd5835ba7f8d7d43bc4228fafd593404ce26b3cc302c6d1fefe65b81 SHA1: 5152b637e1e542025f7e7a1fc5f8d7f0b463dc93 MD5sum: a570c4ca4f2cd71039e150182d28a41d Description: low-level implementations and bindings for pandas This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 2 version. Python-Version: 2.7 Package: python-pyepl Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1460 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), python-pyepl-common (= 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1), python-numpy, python-imaging, python-pygame, python-pyode, python-opengl, ttf-dejavu, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libode4, libsamplerate0 (>= 0.1.7), libsndfile1 (>= 1.0.20), libstdc++6 (>= 5.2) Conflicts: python2.3-pyepl, python2.4-pyepl Replaces: python2.3-pyepl, python2.4-pyepl Provides: python2.7-pyepl Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_amd64.deb Size: 286430 SHA256: ff44ddb8f59b4fdd857e6eadaed6e9313e56685f2a71adc722094105ce169555 SHA1: 5e364e5bb62ff1ddafbbe127422709cf7302e5a5 MD5sum: 48837816129adc541de9665f48eb9d20 Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides PyEPL for supported versions of Python. Package: python-pyepl-common Source: pyepl Version: 1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 822 Depends: neurodebian-popularity-contest, python Homepage: http://pyepl.sourceforge.net/ Priority: optional Section: python Filename: pool/main/p/pyepl/python-pyepl-common_1.1.0+git12-g365f8e3-2~nd+1+nd16.04+1_all.deb Size: 819350 SHA256: 2e955547503f670039815376e4ac8860679cb376009788bc07c133ad3cf0dc02 SHA1: 349b67ae265dd0cbb576d6f2cc991cb1b9582a46 MD5sum: d7b4b656eb6f9dacf1c258cfa9df35bb Description: module for coding psychology experiments in Python PyEPL is a stimuli delivery and response registration toolkit to be used for generating psychology (as well as neuroscience, marketing research, and other) experiments. . It provides - presentation: both visual and auditory stimuli - responses registration: both manual (keyboard/joystick) and sound (microphone) time-stamped - sync-pulsing: synchronizing your behavioral task with external acquisition hardware - flexibility of encoding various experiments due to the use of Python as a description language - fast execution of critical points due to the calls to linked compiled libraries . This toolbox is here to be an alternative for a widely used commercial product E'(E-Prime) . This package provides common files such as images. Package: python-scikits-learn Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 65 Depends: neurodebian-popularity-contest, python-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: oldlibs Filename: pool/main/s/scikit-learn/python-scikits-learn_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 56050 SHA256: 45adc827b4aa2474390176c25d13dc3446faa326e86319af3f008f496006af30 SHA1: 6338a6ab54c6a7239cdf79ba9748675bea42906d MD5sum: dfbe4583cca67c94614c0005eee8e8b7 Description: transitional compatibility package for scikits.learn -> sklearn migration Provides old namespace (scikits.learn) and could be removed if dependent code migrated to use sklearn for clarity of the namespace. Package: python-six Source: six Version: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python-six_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 11102 SHA256: e53e9566f3e3305d5ec1a8b3ed6a12f61a5f0d3279112666903e47ce68c4498c SHA1: e2e8f56e31d6f67994297cf8ef87bd10077f81b0 MD5sum: 19367b5b0032f4ee89cd3f543ed27e5d Description: Python 2 and 3 compatibility library (Python 2 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 2 module path. It is complemented by python3-six. 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Package: python-sklearn Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5283 Depends: neurodebian-popularity-contest, python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-sklearn-lib (>= 0.17.1-1~nd+1+nd16.04+1), python-joblib (>= 0.9.2) Recommends: python-nose, python-matplotlib Suggests: python-dap, python-scikits-optimization, python-sklearn-doc, ipython Enhances: python-mdp, python-mvpa2 Breaks: python-scikits-learn (<< 0.9~) Replaces: python-scikits-learn (<< 0.9~) Provides: python2.7-sklearn Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 1223586 SHA256: e3fc7a163df7f54a06719b94aaa8ae8a4fc13dd993db77e4d940c5885e90272c SHA1: c0aa990dd46f5fd4f68f524715831ca16b93c2f9 MD5sum: 1e29d4471ec9083dbe27a0022a2a961c Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) Package: python-sklearn-doc Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24874 Depends: neurodebian-popularity-contest, libjs-jquery, libjs-underscore Suggests: python-sklearn Conflicts: python-scikits-learn-doc Replaces: python-scikits-learn-doc Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: doc Filename: pool/main/s/scikit-learn/python-sklearn-doc_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 4018952 SHA256: 2267e9c87f930981ff8e6dbaeb57c3dc0162b9c64ab2a7f2f8616ba16686f6cb SHA1: 5b8788a060ca872bf02e4b506c47f46f289384c9 MD5sum: 892cb3b87ccf35037b122e6e74effe21 Description: documentation and examples for scikit-learn This package contains documentation and example scripts for python-sklearn. Package: python-sklearn-lib Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5013 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~) Conflicts: python-scikits-learn-lib Replaces: python-scikits-learn-lib Provides: python2.7-sklearn-lib Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python-sklearn-lib_0.17.1-1~nd+1+nd16.04+1_amd64.deb Size: 1112354 SHA256: 9498f6684d59759849ffaccd033ee12ad91a3d616669a4010fdedec873b73422 SHA1: 80d5693388da8155e2ff1cb32dffaba64530439b MD5sum: f0dc3fb3c1c70943cfcdf72b2cc364a3 Description: low-level implementations and bindings for scikit-learn This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. Package: python-smmap Version: 0.9.0-3~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 90 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8) Suggests: python-nose Provides: python2.7-smmap Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python-smmap_0.9.0-3~nd+1+nd16.04+1_all.deb Size: 20198 SHA256: 37f7091dea7505df24c110b49803dc180666fb029226d920c1ed081d0bc5063c SHA1: 1c047a11bc08e73e4ea2c266b23a77b4b01d3b96 MD5sum: 6c69e2e20aaa72a6d5e0acd5c2483789 Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 2. Package: python-stfio Source: stimfit Version: 0.15.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1373 Depends: neurodebian-popularity-contest, python (<< 2.8), python (>= 2.7), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod3.0.6, libfftw3-double3, libgcc1 (>= 1:3.0), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4), libsuitesparse-dev, zlib1g-dev Recommends: python-matplotlib, python-scipy, python-pandas Provides: python2.7-stfio Homepage: http://www.stimfit.org Priority: optional Section: python Filename: pool/main/s/stimfit/python-stfio_0.15.2-1~nd+1+nd16.04+1_amd64.deb Size: 481502 SHA256: 0289747e603ebdf884342130ffb5b07ca568460c26148084df1dc44ffb4e9942 SHA1: 142ffb5c820fb134642287a818a57f8e3236bc15 MD5sum: 67f0fd8d505b5fade315c183ee99ca77 Description: Python module to read common electrophysiology file formats. The stfio module allows you to read common electrophysiology file formats from Python. Axon binaries (abf), Axon text (atf), HEKA (dat), CFS (dat/cfs), Axograph (axgd/axgx) are currently supported. Package: python-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python-contextlib2, python-mock, python-six (>= 1.5), python-wrapt, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43580 SHA256: d13dfc1adc96024f35330d4c72825e3f09b9767177330c804cc3575079e11498 SHA1: 38af2662eef11399c694c53bdca1e4159e830bc8 MD5sum: 212bc7388c199867c3f9d80be6d829c2 Description: record and replay HTML interactions (Python library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 2. Package: python-vtk-dicom Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 494 Depends: neurodebian-popularity-contest, python (>= 2.7), python (<< 2.8), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libpython2.7 (>= 2.7), libstdc++6 (>= 4.1.1), libvtk-dicom0.5, libvtk5.10, python-vtk Provides: python2.7-vtk-dicom Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: python Filename: pool/main/v/vtk-dicom/python-vtk-dicom_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 90490 SHA256: 72d4bc52366ba201df84aac1235c23b8b381f81113d7b854d673b15f17923672 SHA1: 87f9509347df7df8a1d83a6d18c1fb605416e4d2 MD5sum: 913cdb7893a354206416631b4a424e89 Description: DICOM for VTK - python This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Python 2.x bindings Package: python3-argcomplete Source: python-argcomplete Version: 1.0.0-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 96 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Priority: optional Section: python Filename: pool/main/p/python-argcomplete/python3-argcomplete_1.0.0-1~nd+1+nd16.04+1_all.deb Size: 21058 SHA256: c93bdaf1b23b65d220a8c08b7043df874b281287d7145de0427dd1c2234f151d SHA1: 16ffed2622ee3e42555797e3f02591e8097e9419 MD5sum: 9fb059ae75b85aec11d96ed5c6c686ed Description: bash tab completion for argparse (for Python 3) Argcomplete provides easy, extensible command line tab completion of arguments for your Python script. . It makes two assumptions: . * You're using bash as your shell * You're using argparse to manage your command line arguments/options . Argcomplete is particularly useful if your program has lots of options or subparsers, and if your program can dynamically suggest completions for your argument/option values (for example, if the user is browsing resources over the network). . This package provides the module for Python 3.x. Package: python3-git Source: python-git Version: 2.0.2-1~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1567 Depends: neurodebian-popularity-contest, git (>= 1:1.7) | git-core (>= 1:1.5.3.7), python3-gitdb (>= 0.6.4), python3:any (>= 3.3.2-2~) Suggests: python-git-doc Homepage: https://github.com/gitpython-developers/GitPython Priority: optional Section: python Filename: pool/main/p/python-git/python3-git_2.0.2-1~nd16.04+1_all.deb Size: 288842 SHA256: d76f1c9a484353c059c38ce441201d1c911503110d111e081ac04b74197d41a5 SHA1: c7e20620b35135f744b8bd9c8bdfcc86360b6fd5 MD5sum: f2e1480f0e385c449b04876cc75977cd Description: Python library to interact with Git repositories - Python 3.x python-git provides object model access to a Git repository, so Python can be used to manipulate it. Repository objects can be opened or created, which can then be traversed to find parent commit(s), trees, blobs, etc. . This package provides the Python 3.x module. Package: python3-lda Source: lda Version: 1.0.2-9~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 1315 Depends: neurodebian-popularity-contest, python3 (<< 3.6), python3 (>= 3.5~), python3-numpy, python3-pbr, libc6 (>= 2.14) Homepage: https://pythonhosted.org/lda/ Priority: optional Section: python Filename: pool/main/l/lda/python3-lda_1.0.2-9~nd+1+nd16.04+1_amd64.deb Size: 237590 SHA256: 3cbb50f7352930b20c44343c5db4893215525ba2e4369e11d24f526eb002d553 SHA1: 9de3bab95047a3e29eb367af3fbabff08a63e25d MD5sum: 0c9dbd6e2e513ff2b5045bc672c1783f Description: Topic modeling with latent Dirichlet allocation lda implements latent Dirichlet allocation (LDA) using collapsed Gibbs sampling. . This package contains the Python 3.x module. Package: python3-openpyxl Source: openpyxl Version: 2.3.0-2~nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 1319 Depends: neurodebian-popularity-contest, python3-jdcal, python3:any (>= 3.3.2-2~), python3-lxml (>= 3.3.4) | python3-et-xmlfile Recommends: python3-pytest, python3-pil Homepage: http://bitbucket.org/openpyxl/openpyxl/ Priority: optional Section: python Filename: pool/main/o/openpyxl/python3-openpyxl_2.3.0-2~nd16.04+1_all.deb Size: 198366 SHA256: fdbf672443fd6a1fef2972081a62e73df077d6df43362d6bb9c4103d82bb2bff SHA1: 7da58edb8f3231d5a648b5ea1f8d82c778ec35b9 MD5sum: bd9936151cca80596c5a727f5cf04c02 Description: module to read/write OpenXML xlsx/xlsm files Openpyxl is a pure Python module to read/write Excel 2007 (OpenXML) xlsx/xlsm files. Package: python3-pandas Source: pandas Version: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 13060 Depends: neurodebian-popularity-contest, python3-dateutil, python3-numpy (>= 1:1.7~), python3-tz, python3:any (>= 3.3.2-2~), python3-pandas-lib (>= 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1), python3-pkg-resources, python3-six Recommends: python3-scipy, python3-matplotlib, python3-numexpr, python3-tables, python3-bs4, python3-html5lib, python3-lxml Suggests: python-pandas-doc Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_all.deb Size: 1761432 SHA256: 47eaf5435943a88f6ca141d87147cb81b9a448e42cd8ca25d25bae5d91f3c99e SHA1: 5e256387804735d943b9b94c1041e36224adeb03 MD5sum: 023e7c3f64cf123f9865cf60bc94af4d Description: data structures for "relational" or "labeled" data - Python 3 pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. pandas is well suited for many different kinds of data: . - Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet - Ordered and unordered (not necessarily fixed-frequency) time series data. - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels - Any other form of observational / statistical data sets. The data actually need not be labeled at all to be placed into a pandas data structure . This package contains the Python 3 version. Package: python3-pandas-lib Source: pandas Version: 0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 6033 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://pandas.sourceforge.net Priority: optional Section: python Filename: pool/main/p/pandas/python3-pandas-lib_0.18.0+git114-g6c692ae-1~nd+1+nd16.04+1_amd64.deb Size: 1545030 SHA256: b1b423c0ba033d0df5c3eb661c475e53c825ec81fdbca5eff23e3a2e60ef1edd SHA1: 1aaa4f5a29e406b4a6d7b3f7d3c5a2018a0e3b32 MD5sum: ceb9a5cb4cda278b9927ba94613d893a Description: low-level implementations and bindings for pandas - Python 3 This is an add-on package for python-pandas providing architecture-dependent extensions. . This package contains the Python 3 version. Package: python3-six Source: six Version: 1.9.0-3~bpo8+1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 49 Depends: neurodebian-popularity-contest, python3:any (>= 3.4~) Multi-Arch: foreign Homepage: http://pythonhosted.org/six/ Priority: optional Section: python Filename: pool/main/s/six/python3-six_1.9.0-3~bpo8+1~nd+1+nd16.04+1_all.deb Size: 11162 SHA256: de89c30fb266478195674d595d12a1513db7e2956c8af953ce1f2720e45d4ad9 SHA1: 4c90cc7b7fc37bedacd44c403965b35de5a1751b MD5sum: ab68168bc1f5b17416eb4c2f602f33a3 Description: Python 2 and 3 compatibility library (Python 3 interface) Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. . This package provides Six on the Python 3 module path. It is complemented by python-six. Package: python3-sklearn Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 5282 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~), python3-numpy, python3-scipy, python3-sklearn-lib (>= 0.17.1-1~nd+1+nd16.04+1), python3-joblib (>= 0.9.2) Recommends: python3-nose, python3-matplotlib Suggests: python3-dap, python-sklearn-doc, ipython3 Enhances: python3-mdp, python3-mvpa2 Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn_0.17.1-1~nd+1+nd16.04+1_all.deb Size: 1223126 SHA256: 3b28b162208fa5b5f7235a0fbc97bed0f84e4275c4cb26bc8ed0565b40c7937b SHA1: 406b42aa243cabebfdb495f02e24f0871fa9c5df MD5sum: eeb95f2492c4d2fea8c7c02d99d5b94b Description: Python modules for machine learning and data mining scikit-learn is a collection of Python modules relevant to machine/statistical learning and data mining. Non-exhaustive list of included functionality: - Gaussian Mixture Models - Manifold learning - kNN - SVM (via LIBSVM) . This package contains the Python 3 version. Package: python3-sklearn-lib Source: scikit-learn Version: 0.17.1-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 4593 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~) Homepage: http://scikit-learn.sourceforge.net Priority: optional Section: python Filename: pool/main/s/scikit-learn/python3-sklearn-lib_0.17.1-1~nd+1+nd16.04+1_amd64.deb Size: 1042724 SHA256: ad80a38873a9a81458685552b594ab1db2d8ebb4b78fd7efd03893c7f5b67f55 SHA1: 9cc0134eede4c525fd1a4f09481be06a0baa0554 MD5sum: 371b3fa891e55dfe77654b301803f5dc Description: low-level implementations and bindings for scikit-learn - Python 3 This is an add-on package for python-sklearn. It provides low-level implementations and custom Python bindings for the LIBSVM library. . This package contains the Python 3 version. Package: python3-smmap Source: python-smmap Version: 0.9.0-3~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 90 Depends: neurodebian-popularity-contest, python3:any (>= 3.3.2-2~) Suggests: python3-nose Homepage: https://github.com/Byron/smmap Priority: extra Section: python Filename: pool/main/p/python-smmap/python3-smmap_0.9.0-3~nd+1+nd16.04+1_all.deb Size: 20284 SHA256: bfa892cc23a05905952f05183485a112e9aed4c5b0386ebf8c08e72cf9e87a06 SHA1: 9e20c8d297d9788e3b08ec4aa7e00e980e05606c MD5sum: f14ccea8516ee46232a99dac3d53ca3d Description: pure Python implementation of a sliding window memory map manager Smmap wraps an interface around mmap and tracks the mapped files as well as the amount of clients who use it. If the system runs out of resources, or if a memory limit is reached, it will automatically unload unused maps to allow continued operation. . This package for Python 3. Package: python3-vcr Source: vcr.py Version: 1.7.3-1.0.1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 157 Depends: neurodebian-popularity-contest, python3-six (>= 1.5), python3-wrapt, python3-yaml, python3:any (>= 3.3.2-2~) Homepage: https://github.com/kevin1024/vcrpy/ Priority: optional Section: python Filename: pool/main/v/vcr.py/python3-vcr_1.7.3-1.0.1~nd+1+nd16.04+1_all.deb Size: 43654 SHA256: 18be5074cff6cd48dd691e1921cc15a96ad10de55944bad110958f0842ca8628 SHA1: 4de90dcf566f64fceaaa00a00af8fe588e105295 MD5sum: 4bb489a1b4d0759306109fcd31ec7e58 Description: record and replay HTML interactions (Python3 library) vcr.py records all interactions that take place through the HTML libraries it supports and writes them to flat files, called cassettes (YAML format by default). These cassettes could be replayed then for fast, deterministic and accurate HTML testing. . vcr.py supports the following Python HTTP libraries: - urllib2 (stdlib) - urllib3 - http.client (Python3 stdlib) - Requests - httplib2 - Boto (interface to Amazon Web Services) - Tornado's HTTP client . This package contains the modules for Python 3. Package: spm8-common Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 19186 Depends: neurodebian-popularity-contest Recommends: spm8-data, spm8-doc Priority: extra Section: science Filename: pool/main/s/spm8/spm8-common_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 9781970 SHA256: 30cac74b9ad9db32f093eece5bae13d28ce4e1222878358f3afc6e6a67b55b67 SHA1: 4899f3ba6a1ff156b67ed1b324ae4a83ffbbab9e MD5sum: 093fd447d8b43ebafc21585625545b37 Description: analysis of brain imaging data sequences Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the platform-independent M-files. Package: spm8-data Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 73019 Depends: neurodebian-popularity-contest Priority: extra Section: science Filename: pool/main/s/spm8/spm8-data_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 45497774 SHA256: bde3c93b9c1168ff6fa5b3269782006cf5613ba3f2b7b49abd5249d07600335b SHA1: af6dce85c4ee9079c720d544dfacfe2fc2cffa67 MD5sum: 494ca73671489f3feaf525e4295caff3 Description: data files for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provide the data files shipped with the SPM distribution, such as various stereotaxic brain space templates and EEG channel setups. Package: spm8-doc Source: spm8 Version: 8.5236~dfsg.1-1~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Team Installed-Size: 9251 Depends: neurodebian-popularity-contest Priority: extra Section: doc Filename: pool/main/s/spm8/spm8-doc_8.5236~dfsg.1-1~nd+1+nd16.04+1_all.deb Size: 8934936 SHA256: 7f6f08608f31115b8e51d149f8560a2cfe399bd44562ff34bf2aeb24a9632bc9 SHA1: 31e802efc7a2237d47eb5a13d1d6f6a6f9ed7324 MD5sum: c96ec4b1e942cf1f8f8eb55b327d7c40 Description: manual for SPM8 Statistical Parametric Mapping (SPM) refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional brain imaging data. These ideas have been instantiated in software that is called SPM. It is designed for the analysis of fMRI, PET, SPECT, EEG and MEG data. . This package provides the SPM manual in PDF format. Package: stimfit Version: 0.15.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 3219 Depends: neurodebian-popularity-contest, libblas3 | libblas.so.3, libc6 (>= 2.14), libcholmod3.0.6, libfftw3-double3, libgcc1 (>= 1:3.0), libhdf5-10, liblapack3 | liblapack.so.3, libpython2.7 (>= 2.7), libstdc++6 (>= 5.2), libwxbase3.0-0v5 (>= 3.0.2+dfsg), libwxgtk3.0-0v5 (>= 3.0.2+dfsg), zlib1g (>= 1:1.1.4), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python2.7, python:any (>= 2.6.6-7~), libsuitesparse-dev, zlib1g-dev, python-wxgtk3.0 | python-wxgtk2.8 (>= 2.8.9), python-matplotlib Recommends: python-scipy Homepage: http://www.stimfit.org Priority: optional Section: science Filename: pool/main/s/stimfit/stimfit_0.15.2-1~nd+1+nd16.04+1_amd64.deb Size: 918846 SHA256: 43ad8f98dc1a369cbac120399ad1ac6102d51e76456e98c82a93a85525f51d4b SHA1: 5f0218bbe21969d5d931ecdb91f28b87b3ba8ab2 MD5sum: 3ba957bbc4d88ff32367b79d1e65ae72 Description: Program for viewing and analyzing electrophysiological data Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. Package: stimfit-dbg Source: stimfit Version: 0.15.2-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 30607 Depends: neurodebian-popularity-contest, stimfit Recommends: python-matplotlib, python-scipy, python-stfio Homepage: http://www.stimfit.org Priority: extra Section: debug Filename: pool/main/s/stimfit/stimfit-dbg_0.15.2-1~nd+1+nd16.04+1_amd64.deb Size: 6597970 SHA256: 35a7443a65b3bc7c43889e8fbc6f088ec0bd5b9bb57ac106c9cf31d9cf7d8cba SHA1: 928ef35555a47743b28106233d95837ff230ab29 MD5sum: e8ba1c05394998d040cf8e8dc2976a2d Description: Debug symbols for stimfit Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy. This package contains the debug symbols for Stimfit. Package: ubuntu-keyring Version: 2010.+09.30~nd+1+nd16.04+1 Architecture: all Maintainer: NeuroDebian Maintainers Installed-Size: 24 Recommends: gpgv Priority: important Section: misc Filename: pool/main/u/ubuntu-keyring/ubuntu-keyring_2010.+09.30~nd+1+nd16.04+1_all.deb Size: 11702 SHA256: e6052ad683b7b3eac5152f3790fcf69f3340f2526d81e9e394a6c4b11fbb26c0 SHA1: 288fe25a2be199481113954438cd17bc01060293 MD5sum: f432078db30b3298f5dbac78eaad7c06 Description: GnuPG keys of the Ubuntu archive The Ubuntu project digitally signs its Release files. This package contains the archive keys used for that. Package: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 348 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 4.2.1), libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: utils Filename: pool/main/v/vrpn/vrpn_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 47934 SHA256: e6f7ac1d6920c0f57691c048d994c9e901daf9c718e6d44c2ca599f7a1595cc5 SHA1: ac39f456fe7fdf65d170e3aa9817c67d4b0c64bf MD5sum: 01520507139dfcc92a73d7239e11df86 Description: Virtual Reality Peripheral Network (executables) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the executables like the VRPN server. Package: vrpn-dbg Source: vrpn Version: 07.30+dfsg-1~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 5172 Depends: neurodebian-popularity-contest, libvrpn0 (= 07.30+dfsg-1~nd+1+nd16.04+1), libvrpnserver0 (= 07.30+dfsg-1~nd+1+nd16.04+1), vrpn (= 07.30+dfsg-1~nd+1+nd16.04+1) Homepage: http://www.cs.unc.edu/Research/vrpn/ Priority: extra Section: debug Filename: pool/main/v/vrpn/vrpn-dbg_07.30+dfsg-1~nd+1+nd16.04+1_amd64.deb Size: 1077458 SHA256: f556bb2601abba9acfa62fe935a6d0c259ba1efee3868b658ec5999a58e9223a SHA1: d60d891faa6da3842f7132b841c499c3a8b931e7 MD5sum: 7259b2bb3fb5c5ec3dcf19296bb5ecea Description: Virtual Reality Peripheral Network (debugging symbols) The Virtual-Reality Peripheral Network (VRPN) is a set of classes within a library and a set of servers that are designed to implement a network-transparent interface between application programs and the set of physical devices (tracker, etc.) used in a virtual-reality (VR) system. The idea is to have a PC or other host at each VR station that controls the peripherals (tracker, button device, haptic device, analog inputs, sound, etc). VRPN provides connections between the application and all of the devices using the appropriate class-of-service for each type of device sharing this link. The application remains unaware of the network topology. Note that it is possible to use VRPN with devices that are directly connected to the machine that the application is running on, either using separate control programs or running all as a single program. . This package contains the debugging symbols of the libraries and executables. Package: vtk-dicom-tools Source: vtk-dicom Version: 0.5.5-2~nd+1+nd16.04+1 Architecture: amd64 Maintainer: NeuroDebian Maintainers Installed-Size: 292 Depends: neurodebian-popularity-contest, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libvtk-dicom0.5, libvtk5.10 Homepage: http://github.com/dgobbi/vtk-dicom/ Priority: optional Section: utils Filename: pool/main/v/vtk-dicom/vtk-dicom-tools_0.5.5-2~nd+1+nd16.04+1_amd64.deb Size: 74420 SHA256: 92f477592c081c6845f6543d159cbf8bc61fe9a546f7f76368e98389b8c4ce47 SHA1: 654070e833e6bae0221c6cad237485d14ae991af MD5sum: 077421e9c48bf947c2eb4aacd390092a Description: DICOM for VTK - tools This package contains a set of classes for managing DICOM files and metadata from within VTK, and some utility programs for interrogating and converting DICOM files. . Command line tools